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September 10, 2025IAA Journal of Biological Sciences

Addressing Bias in AI Algorithms for Health Applications

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Authors

KAKansiime Agnes

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Overview

This review analyzes AI bias in health applications, highlighting disparities and exploring mitigation strategies.

Key Points

  • Bias in AI has led to unequal treatment recommendations, causing disparities in healthcare outcomes.
  • Imbalanced training datasets and flawed algorithm design contribute significantly to biases in health AI.
  • The review examines successful case studies aimed at improving fairness and trust in medical AI systems.
  • Establishing bias-resilient AI frameworks is crucial for achieving equitable health outcomes in digital health.

Cite This Study

Kansiime Agnes (2025) studied this question.

synapsesocial.com/papers/68c23fc3b210217d6479835fhttps://doi.org/10.59298/iaajb/2025/1313743
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